Transcript Introduction - San Jose State University

MET 112 Global Climate Change - Lecture 11
Future Predictions
Craig Clements
San Jose State University
Climate Change and humans
 Anthropogenic increases in
– greenhouse-gas concentrations
– sulfate aerosols due to anthropogenic
emissions
 Emission scenarios have been developed
 Changes in solar irradiance and volcanic
aerosols
– Unpredictable and difficult to model
Q: How do we predict what the
future climate will be like?
A: We use global models of the
earth system
Global Climate Models (GCMs)
Sequence of Steps
1. Estimate future GHGs concentration
2. Using future GHG levels, calculate what
future climate (e.g. temp, precip) will be
like.
3. Assess the uncertainty of the predictions
Calculation of Future CO2
Concentrations
CO2 Emissions -How
much is going into
atmosphere
Carbon Cycle Model –
Simulates atmosphere-biosphere
and atmosphere-ocean interactions
CO2 Concentration How much remains in
atmosphere
Carbon Cycle Models
 Atmosphere/ocean and atmosphere/biosphere
interactions not well understood
 Model calculations contain uncertainty; the
largest uncertainty:
– Future uptake of carbon by the biosphere
– Future uptake of carbon by the oceans
Past and Projected Future CO2
(ppm) Parts per million
Concentrations (Back-Up)
Observations
Model
projections
What factors affect future CO2 levels?





Global Population
Type of energy generation
– Fossil intensive
– Renewable energy
Growth of Economy
Type of Economy
– Material based
– Service and information based
Cooperation among countries
– More homogeneous - share technologies
– More isolated - larger divide between rich/poor
countries
The IPCC based its projections on six emission scenarios,
running each one through sophisticated climate simulation
programs.
A1B
A1FI
A1T
Economic
A1
Governance
Global
B1
Development
Environmental
A2
B2
Local
Adapted from Arnell et al.
(2004). Global Environmental
Change, 14:3-20
Gross Domestic Product Growth at 2100
A1
Economic
Governance
Global
B1
Development
Environmental
A2
B2
Local
Adapted from Arnell et al.
(2004). Global Environmental
Change, 14:3-20
Energy Use at 2100
A1
Economic
Governance
Global
B1
Development
Environmental
A2
B2
Local
Adapted from Arnell et al.
(2004). Global Environmental
Change, 14:3-20
Technological Change at 2100
A1B
A1T
Economic
Country A
Country B
Global
Governance
A1FI
B1
Development
Environmental
A2
Country C
B2
Local
Adapted from Arnell et al.
(2004). Global Environmental
Change, 14:3-20
Scenarios (1)
Scenarios (2)
 A1 storyline
– World of rapid economic growth
– Population peaks 2050
– Different branches dependent on energy type/use
 A1FI – Fossil intensive – continued dependence on
coal/oil
 A1T – Non-fossil intensive energy use (Technology)
 A1B – Balance between fossil and non-fossil
 A2 storyline
– Heteorogenous world –technologies are not shared
across borders,
– population continues to increase
Scenarios (3)
 B1 storyline
– Similar population as A1
– Global exchange/cooperation
– Change in economic structures from product
oriented to service oriented.
– Focus on social and economic sustainability
 B2 storyline
– Population like A2
– Similar environmental and social focus
– More regionally oriented (not as much
exchange between countries).
CO2 emissions for various scenarios
Why a peak around 2050?
Note:
global
population
peaks in
2050 and
declines in
some
scenarios
Projected CO2 Concentrations for
Various Scenarios
 Note that even the low-emission scenarios result in
greatly increased CO2 concentrations by the year
2100
– Max concentration (of scenarios shown): 970 ppm
– Min concentration (of scenarios shown): 550 ppm
– (Compare with current value: 370 ppm)
Climate Model
 A climate model is a mathematical
representation of the physical processes that
control climate
– Basically everything that affects climate
– Sun, atmosphere (greenhouse gases,
aerosols), hydrosphere, land surface,
cryosphere
 Equations are very complicated
– Some of the world’s largest supercomputers
are running climate models
Climate Modeling: Super Computers
One frame of an IBM Power5-575
series system. NCAR's “Blue Vista”
will have 16 frames.
Blue Vista will need over
250 kilowatts of power to operate.
The average personal computer
consumes 0.12 kilowatts .
78 IBM POWER5 nodes.
Each node will have eight POWER5
simultaneous multithreading (SMT)
processors
16 gigabytes of memory.
NCAR’s “Blue Vista” IBM Power5
Model Schematic
Changes in greenhouse-gas
concentrations and changes
in albedo due to aerosols
Climate Model
Climate change
(i.e. temperature,
precipitation etc.)
Model Sensitivity
 Models (like the atmosphere) are sensitive
systems.
 They can respond differently to the same
radiative forcing, e.g., a doubling of CO2
– This means that different models give
different answers to the same problem
– Thus, we use a range of models to determine
the range of possible future scenarios.
Model Verification: Can it be done?
 Before you can trust any of these models, they
must be verified.
– We can use past climate as a test.
If your model can simulate the past climate,
then there is a reasonable chance that the
model can accurately predict future
climate.
Can we predict changes in past climate?
Global Average Surface Temperature
Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers.
Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers.
These experiments demonstrate that
1. The warming of the entire 20th
century is largely due to humans
2. The warming of the last 50 years is
largely due to humans.
3. Natural factors are largely
responsible for the warming of the
20th century
4. Natural factors are not important in
the early 20th century, but more
important in the last part of the 20th
century.
Climate models
1.
2.
3.
4.
Are not useful for predicting the temperature
changes observed during the 20th century.
Show that volcanic eruptions and changes in
sunlight are responsible for most of the
changes observed over the 20th century.
Can predict the 20th century observed
temperature changes with natural factors only.
Can only predict the 20th century observed
temperature changes when they include both
human and natural contributions.
What conclusions can you infer from these
model experiments?
1. Models can reasonably predict
temperature variations over the last
150 years.
2. Most of the observed warming in the
past 50 years is attributable to human
activities.
Carbon Emissions
UNEP 2003
Notes on Temperature Projections
 Projected Warming: 2000 – 2100 ranges from
~1.4°C to ~5.8°C.
 Curves represent warming produced for seven
scenarios by a model with average sensitivity.
 Each bar on the right represents a range of
warming produced
– by models of differing sensitivies for a
specific scenario.
Land areas are projected to warm more than the
oceans with the greatest warming at high latitudes
Annual mean temperature change, 2071 to 2100
relative to 1990: Global Average in 2085 = 3.1oC
Some areas are projected to become wetter,
others drier with an overall increase projected
Annual mean precipitation change: 2071 to 2100
Relative to 1990
Sea Level
Sea Level Rise
Annual mean precipitation change: 2071 to 2100 Relative to 1990
Recent Sea Level Changes
Future predictions: main changes in
climate
 Higher temperatures - especially on land
– Arctic shows the largest warming
 Hydrological cycle more intense
– More rain overall
 Sea levels rise
– Why?
 Changes at regional level –hard to predict
 More intense weather (extremes)
– Floods, droughts etc.
Questions
1. Based on the A1FI scenario, what is the
predicted CO2 concentration, temperature
change and sea level change in 2100?
2. Based on the B1 scenario, what is the
predicted CO2 concentration, temperature
change and sea level change in 2100?
3. Explain the differences.
If CO2 emissions were stabilized at present
day values, CO2 concentrations would
1. Continue to increase
2. Stabilize
3. Start to decrease